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cs.LG2026
GDPO: Mitigating Multi-Reward Conflicts via Group-Dynamic reward-Decoupled Policy Optimization
Haotian Liu, Yihao Liu, Jingwei Ni +11
As LLMs advance, post-training reinforcement learning (RL) increasingly relies on multi-dimensional rewards to cultivate comprehensive capabilities. This shift demands new algorith…
cs.LG2025
CGSPG: Confidence-calibrated Group Sequence Policy Gradient towards Self-aware Reasoning
Haotian Liu, Shuo Wang, Hongteng Xu
Reinforcement Learning (RL) methods, exemplified by Group Relative Policy Optimization (GRPO) and its variants, play a central role in developing reasoning models. However, these m…
cs.LG2024
Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
Shen Yuan, Haotian Liu, Hongteng Xu
While following different technical routes, both low-rank and orthogonal adaptation techniques can efficiently adapt large-scale pre-training models in specific tasks or domains ba…